SOTAVerified

3D Object Detection

3D Object Detection is a task in computer vision where the goal is to identify and locate objects in a 3D environment based on their shape, location, and orientation. It involves detecting the presence of objects and determining their location in the 3D space in real-time. This task is crucial for applications such as autonomous vehicles, robotics, and augmented reality.

( Image credit: AVOD )

Papers

Showing 7180 of 1576 papers

TitleStatusHype
LiDAR-PTQ: Post-Training Quantization for Point Cloud 3D Object DetectionCode2
RoboFusion: Towards Robust Multi-Modal 3D Object Detection via SAMCode2
WidthFormer: Toward Efficient Transformer-based BEV View TransformationCode2
OneFormer3D: One Transformer for Unified Point Cloud SegmentationCode2
FlashOcc: Fast and Memory-Efficient Occupancy Prediction via Channel-to-Height PluginCode2
PonderV2: Pave the Way for 3D Foundation Model with A Universal Pre-training ParadigmCode2
UniPAD: A Universal Pre-training Paradigm for Autonomous DrivingCode2
CoDA: Collaborative Novel Box Discovery and Cross-modal Alignment for Open-vocabulary 3D Object DetectionCode2
SparseBEV: High-Performance Sparse 3D Object Detection from Multi-Camera VideosCode2
UniTR: A Unified and Efficient Multi-Modal Transformer for Bird's-Eye-View RepresentationCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1EA-LSSNDS0.78Unverified
2MMFusion-eNDS0.77Unverified
3MegFusionNDS0.77Unverified
4RacoonPowerNDS0.76Unverified
5BEVFusion-eNDS0.76Unverified
6DeepInteraction-largeNDS0.76Unverified
7DeepInteraction-eNDS0.76Unverified
8DAANDS0.75Unverified
9FusionVPENDS0.75Unverified
10CenterPoint-FusionNDS0.75Unverified